Cluster analysis of transcriptomic datasets to identify endotypes of idiopathic pulmonary fibrosis.
Cluster analysis of transcriptomic datasets to identify endotypes of idiopathic pulmonary fibrosis.
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作者：
特发性肺纤维化（IPF）中相当大的临床异质性表明存在多种疾病内在型。识别这些内型将提高我们对IPF发病机制的理解，并可以允许生物标志物驱动的个性化药物方法。我们的目的是确定可能代表不同疾病内在型的临床不同IPF患者组。我们对三个公开的血液转录组数据集（共220例IPF病例）进行了共标准化、合并和聚类。我们比较了聚类之间的临床特征，并使用基因富集分析来识别在聚类之间差异表达的基因中过度表达的生物学途径和过程。开发了基于基因的分类器，并使用三个额外的独立数据集（共194例IPF病例）进行了验证。我们确定了三组IPF患者，组间肺功能（p=0.009）和死亡率（p=0.009）存在统计学显著差异。基因富集分析暗示线粒体稳态，细胞凋亡，细胞周期和先天性和适应性免疫的发病机制，这些群体的基础。我们开发并验证了一个13基因聚类分类器，该分类器可预测IPF的死亡率（高风险聚类与低风险聚类：HR 4.25，95% CI 2.14至8.46，p=3.7×10−5）。我们已经确定了血液基因表达特征，能够区分具有显著生存差异的IPF患者组。这些聚类可以代表不同的病理生理状态，这将支持IPF的多种内源型理论。虽然还需要做更多的工作来确认这些内型的存在，但我们的分类器可能是IPF患者分层和结局预测的有用工具。
Considerable clinical heterogeneity in idiopathic pulmonary fibrosis (IPF) suggests the existence of multiple disease endotypes. Identifying these endotypes would improve our understanding of the pathogenesis of IPF and could allow for a biomarker-driven personalised medicine approach. We aimed to identify clinically distinct groups of patients with IPF that could represent distinct disease endotypes. We co-normalised, pooled and clustered three publicly available blood transcriptomic datasets (total 220 IPF cases). We compared clinical traits across clusters and used gene enrichment analysis to identify biological pathways and processes that were over-represented among the genes that were differentially expressed across clusters. A gene-based classifier was developed and validated using three additional independent datasets (total 194 IPF cases). We identified three clusters of patients with IPF with statistically significant differences in lung function (p=0.009) and mortality (p=0.009) between groups. Gene enrichment analysis implicated mitochondrial homeostasis, apoptosis, cell cycle and innate and adaptive immunity in the pathogenesis underlying these groups. We developed and validated a 13-gene cluster classifier that predicted mortality in IPF (high-risk clusters vs low-risk cluster: HR 4.25, 95% CI 2.14 to 8.46, p=3.7×10−5). We have identified blood gene expression signatures capable of discerning groups of patients with IPF with significant differences in survival. These clusters could be representative of distinct pathophysiological states, which would support the theory of multiple endotypes of IPF. Although more work must be done to confirm the existence of these endotypes, our classifier could be a useful tool in patient stratification and outcome prediction in IPF.
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DOI：
10.1016/s2213-2600(17)30349-1
发表时间：
2017-11
期刊：
The Lancet. Respiratory medicine
影响因子：
--
作者：
Herazo-Maya JD;Sun J;Molyneaux PL;Li Q;Villalba JA;Tzouvelekis A;Lynn H;Juan-Guardela BM;Risquez C;Osorio JC;Yan X;Michel G;Aurelien N;Lindell KO;Klesen MJ;Moffatt MF;Cookson WO;Zhang Y;Garcia JGN;Noth I;Prasse A;Bar-Joseph Z;Gibson KF;Zhao H;Herzog EL;Rosas IO;Maher TM;Kaminski N
通讯作者：
Kaminski N
影响因子：
17.1
作者：
Sweeney TE;Wong HR;Khatri P
通讯作者：
Khatri P
影响因子：
7.3
作者：
Adegunsoye A;Hrusch CL;Bonham CA;Jaffery MR;Blaine KM;Sullivan M;Churpek MM;Strek ME;Noth I;Sperling AI
通讯作者：
Sperling AI
影响因子：
3
作者：
Rodríguez-Portal JA
通讯作者：
Rodríguez-Portal JA
DOI：
10.3109/08977194.2011.595714
发表时间：
2011-10
期刊：
Growth factors (Chur, Switzerland)
影响因子：
--
作者：
Biernacka A;Dobaczewski M;Frangogiannis NG
通讯作者：
Frangogiannis NG